Search Results for author:
Found 12 papers, 3 papers with code
TableGPT: Towards Unifying Tables, Nature Language and Commands into One GPT
Tables are prevalent in real-world databases, requiring significant time and effort for humans to analyze and manipulate.
LESS: Label-efficient Multi-scale Learning for Cytological Whole Slide Image Screening
We provide appropriate supervision by using slide-level labels to improve the learning of patch-level features.
Learning Trajectory-Conditioned Relations to Predict Pedestrian Crossing Behavior
In smart transportation, intelligent systems avoid potential collisions by predicting the intent of traffic agents, especially pedestrians.
On the Ramifications of Human Label Uncertainty
Our evaluation of existing uncertainty estimation algorithms, with the presence of HLU, indicates the limitations of existing uncertainty metrics and algorithms themselves in response to HLU.
Graph neural networks for materials science and chemistry
Machine learning plays an increasingly important role in many areas of chemistry and materials science, e. g. to predict materials properties, to accelerate simulations, to design new materials, and to predict synthesis routes of new materials.
Application of Quantum Machine Learning using the Quantum Variational Classifier Method to High Energy Physics Analysis at the LHC on IBM Quantum Computer Simulator and Hardware with 10 qubits
On the quantum hardware, the quantum variational classifier method has shown promising discrimination power, comparable to that on the quantum simulator.
Quantum Physics High Energy Physics - Experiment
Training Deep Neural Networks for Wireless Sensor Networks Using Loosely and Weakly Labeled Images
Although deep learning has achieved remarkable successes over the past years, few reports have been published about applying deep neural networks to Wireless Sensor Networks (WSNs) for image targets recognition where data, energy, computation resources are limited.
Augmented Bi-path Network for Few-shot Learning
Finally, the model learns to compare global and local features separately, i. e., in two paths, before merging the similarities.
Towards the Automation of Deep Image Prior
Single image inverse problem is a notoriously challenging ill-posed problem that aims to restore the original image from one of its corrupted versions.
LHC Dark Matter Working Group: Next-generation spin-0 dark matter models
The exclusion limits obtained from the proposed scans can be consistently compared to the constraints on the $\textrm{2HDM+a}$ model that derive from DD, ID and the DM relic density.
High Energy Physics - Experiment High Energy Physics - Phenomenology
Fast, Accurate Thin-Structure Obstacle Detection for Autonomous Mobile Robots
This work is devoted to a task that is indispensable for safety yet was largely overlooked in the past -- detecting obstacles that are of very thin structures, such as wires, cables and tree branches.
Exploiting Object Similarity in 3D Reconstruction
Despite recent progress, reconstructing outdoor scenes in 3D from movable platforms remains a highly difficult endeavour.
